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Course Description

Mathematical reasoning provides the theoretical foundation for artificial intelligence, machine learning, and data science. This course introduces the core mathematical principles that support data-driven modeling and algorithmic decision-making, including calculus, probability, statistics, linear algebra, regression, classification, and neural networks. Students will integrate mathematical theory with computational practice using Python-based tools to analyze data, evaluate models, and interpret the quantitative foundations of common AI and data science methods.

Learner Outcomes

When you complete the course successfully, you will be able to:
  • Apply foundational mathematical concepts, including functions, logarithms, derivatives, and integrals, to problems in AI and data science
  • Use probability theory and probability distributions to model uncertainty and support quantitative reasoning
  • Summarize, visualize, and interpret data using descriptive and inferential statistical methods
  • Conduct hypothesis testing using confidence intervals, p-values, and statistical significance criteria
  • Apply linear algebra concepts, including vectors, matrices, linear transformations, determinants, and eigende composition
  • Develop and interpret regression models using residual analysis, least squares estimation, gradient descent, and model evaluation metrics
  • Explain the mathematical structure of neural networks, including weights, biases, activation functions, forward propagation, backpropagation, and optimization
  • Communicate mathematical, statistical, and computational findings clearly within AI and data science applications

Textbook Information

A textbook is available for this course. 
Click here to view a textbook list for FAES courses and purchasing information. Please note that tuition does not include textbooks.

Prerequisites

Previous academic experience with advanced math areas such as linear algebra, multivariable calculus, and statistics is strongly recommended. 

Refund
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Scholarship and Funding

Are you a self-funded student? FAES offers scholarship options. Click here for more information and to apply. 

Looking for resources to help you acquire funding for your continued education? Click here for our funding justification guide. 

Photo Release

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Section Title
Essential Math for AI and Data Science
Type
Online Asynchronous
Dates
Aug 26, 2026 to Oct 13, 2026
Total Cost (Includes $100 non-refundable technology fee per course when applicable)
Eligible Discounts Can Be Applied at Checkout (2 Credits) $800.00
Potential Discount(s)
Available for Academic Credit
2 Credit(s)
Instructor(s)
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